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PREDICTIVE REAL TIME CONTROL OF SURCHARGED INTERCEPTORS: IMPACT OF SEVERAL CONTROL PARAMETERS<sup>1</sup>

2003· article· en· W2002866898 on OpenAlexafffundabout
Sophie Duchesne, Alain Mailhot, Jean‐Pierre Villeneuve

Bibliographic record

VenueJAWRA Journal of the American Water Resources Association · 2003
Typearticle
Languageen
FieldEnvironmental Science
TopicUrban Stormwater Management Solutions
Canadian institutionsGDG EnvironnementInstitut National de la Recherche Scientifique
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsEnvironmental scienceCombined sewerModel predictive controlControl (management)Hydrology (agriculture)Sanitary sewerHorizonFlow (mathematics)Electrical conduitEnvironmental engineeringEngineeringComputer scienceGeotechnical engineeringMathematicsTelecommunications

Abstract

fetched live from OpenAlex

ABSTRACT: A global predictive real time control strategy minimizing overflow volumes from combined sewers during rainfall was applied to control flows entering the Marigot interceptor (Laval, Canada) for 23 rain events that occurred in this urban area during the summer of 1989. Different surcharge intensities were allowed in the sewer. The duration of the control horizon as well as the location and number of control regulators were varied to assess the impact of these parameters on total overflow volumes and on control safety. Due to the high propagation speed of flow waves in pressurized conduits, it was found that five‐ minute control horizons were sufficient to ensure control performance and safety when important surcharges were permitted in the interceptor and when the controlled regulators were located where pressurized flow occurred. It was also found that it is possible to reduce the number of controlled regulators by placing them at locations intercepting the largest volumes of water during rain periods.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.140
Threshold uncertainty score0.445

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.004
GPT teacher head0.204
Teacher spread0.200 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations5
Published2003
Admission routes3
Has abstractyes

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